diff --git a/monai/transforms/spatial/array.py b/monai/transforms/spatial/array.py index b6bf211cc4..55dab79c3d 100644 --- a/monai/transforms/spatial/array.py +++ b/monai/transforms/spatial/array.py @@ -1848,7 +1848,7 @@ def __init__( """ Args: rotate_range: angle range in radians. If element `i` is a pair of (min, max) values, then - `uniform[-rotate_range[i][0], rotate_range[i][1])` will be used to generate the rotation parameter + `uniform[rotate_range[i][0], rotate_range[i][1])` will be used to generate the rotation parameter for the `i`th spatial dimension. If not, `uniform[-rotate_range[i], rotate_range[i])` will be used. This can be altered on a per-dimension basis. E.g., `((0,3), 1, ...)`: for dim0, rotation will be in range `[0, 3]`, and for dim1 `[-1, 1]` will be used. Setting a single value will use `[-x, x]` @@ -2386,7 +2386,7 @@ def __init__( prob: probability of returning a randomized affine grid. defaults to 0.1, with 10% chance returns a randomized grid. rotate_range: angle range in radians. If element `i` is a pair of (min, max) values, then - `uniform[-rotate_range[i][0], rotate_range[i][1])` will be used to generate the rotation parameter + `uniform[rotate_range[i][0], rotate_range[i][1])` will be used to generate the rotation parameter for the `i`th spatial dimension. If not, `uniform[-rotate_range[i], rotate_range[i])` will be used. This can be altered on a per-dimension basis. E.g., `((0,3), 1, ...)`: for dim0, rotation will be in range `[0, 3]`, and for dim1 `[-1, 1]` will be used. Setting a single value will use `[-x, x]` @@ -2656,7 +2656,7 @@ def __init__( defaults to 0.1, with 10% chance returns a randomized elastic transform, otherwise returns a ``spatial_size`` centered area extracted from the input image. rotate_range: angle range in radians. If element `i` is a pair of (min, max) values, then - `uniform[-rotate_range[i][0], rotate_range[i][1])` will be used to generate the rotation parameter + `uniform[rotate_range[i][0], rotate_range[i][1])` will be used to generate the rotation parameter for the `i`th spatial dimension. If not, `uniform[-rotate_range[i], rotate_range[i])` will be used. This can be altered on a per-dimension basis. E.g., `((0,3), 1, ...)`: for dim0, rotation will be in range `[0, 3]`, and for dim1 `[-1, 1]` will be used. Setting a single value will use `[-x, x]` @@ -2824,7 +2824,7 @@ def __init__( defaults to 0.1, with 10% chance returns a randomized elastic transform, otherwise returns a ``spatial_size`` centered area extracted from the input image. rotate_range: angle range in radians. If element `i` is a pair of (min, max) values, then - `uniform[-rotate_range[i][0], rotate_range[i][1])` will be used to generate the rotation parameter + `uniform[rotate_range[i][0], rotate_range[i][1])` will be used to generate the rotation parameter for the `i`th spatial dimension. If not, `uniform[-rotate_range[i], rotate_range[i])` will be used. This can be altered on a per-dimension basis. E.g., `((0,3), 1, ...)`: for dim0, rotation will be in range `[0, 3]`, and for dim1 `[-1, 1]` will be used. Setting a single value will use `[-x, x]` diff --git a/monai/transforms/spatial/dictionary.py b/monai/transforms/spatial/dictionary.py index b811da7f3d..51ad0435fc 100644 --- a/monai/transforms/spatial/dictionary.py +++ b/monai/transforms/spatial/dictionary.py @@ -1061,7 +1061,7 @@ def __init__( prob: probability of returning a randomized affine grid. defaults to 0.1, with 10% chance returns a randomized grid. rotate_range: angle range in radians. If element `i` is a pair of (min, max) values, then - `uniform[-rotate_range[i][0], rotate_range[i][1])` will be used to generate the rotation parameter + `uniform[rotate_range[i][0], rotate_range[i][1])` will be used to generate the rotation parameter for the `i`th spatial dimension. If not, `uniform[-rotate_range[i], rotate_range[i])` will be used. This can be altered on a per-dimension basis. E.g., `((0,3), 1, ...)`: for dim0, rotation will be in range `[0, 3]`, and for dim1 `[-1, 1]` will be used. Setting a single value will use `[-x, x]` @@ -1246,7 +1246,7 @@ def __init__( defaults to 0.1, with 10% chance returns a randomized grid, otherwise returns a ``spatial_size`` centered area extracted from the input image. rotate_range: angle range in radians. If element `i` is a pair of (min, max) values, then - `uniform[-rotate_range[i][0], rotate_range[i][1])` will be used to generate the rotation parameter + `uniform[rotate_range[i][0], rotate_range[i][1])` will be used to generate the rotation parameter for the `i`th spatial dimension. If not, `uniform[-rotate_range[i], rotate_range[i])` will be used. This can be altered on a per-dimension basis. E.g., `((0,3), 1, ...)`: for dim0, rotation will be in range `[0, 3]`, and for dim1 `[-1, 1]` will be used. Setting a single value will use `[-x, x]` @@ -1396,7 +1396,7 @@ def __init__( defaults to 0.1, with 10% chance returns a randomized grid, otherwise returns a ``spatial_size`` centered area extracted from the input image. rotate_range: angle range in radians. If element `i` is a pair of (min, max) values, then - `uniform[-rotate_range[i][0], rotate_range[i][1])` will be used to generate the rotation parameter + `uniform[rotate_range[i][0], rotate_range[i][1])` will be used to generate the rotation parameter for the `i`th spatial dimension. If not, `uniform[-rotate_range[i], rotate_range[i])` will be used. This can be altered on a per-dimension basis. E.g., `((0,3), 1, ...)`: for dim0, rotation will be in range `[0, 3]`, and for dim1 `[-1, 1]` will be used. Setting a single value will use `[-x, x]`